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Modulation Recognition for HF Signals

机译:HF信号的调制识别

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High-frequency (HF) communications is undergoing resurgence despite advances in long-range satellite communication systems. Defense agencies are using the HF spectrum for backup communications as well as for spectrum surveillance applications. Spectrum management organizations are monitoring the HF spectrum to control and enforce licensing. These activities usually require systems capable of determining the location of a source of transmissions, separating valid signals from interference and noise, and recognizing signal modulation. Our ultimate aim is to develop robust modulation recognition algorithms for real HF signals, that is, signals propagating by multiple ionospheric modes. One aspect of modulation recognition is the extraction of signal identifying features. The most common features for modulation recognition are instantaneous phase, amplitude, and frequency. However, this paper focuses on two feature parameters: coherence and entropy. Signal entropy and the coherence function show potential for robust recognition of HF modulation types in the presence of HF noise and multi-path. Specifically, it is shown that the methods of calculation of coherence and entropy are important and that appropriate calculations ensure stability in the parameters. For the first time a new metric, called Coherence-Median Difference (CMD), is introduced that provides a measure of the dominance of coherence at specific frequencies to coherence at all other frequencies in a particular bandwidth.
机译:尽管远程卫星通信系统取得了进步,但高频(HF)通信正在兴起。国防机构正在将HF频谱用于备份通信以及频谱监视应用程序。频谱管理组织正在监视HF频谱,以控制和执行许可。这些活动通常需要能够确定传输源位置,将有效信号与干扰和噪声分离以及识别信号调制的系统。我们的最终目标是为实际的HF信号(即通过多种电离层模式传播的信号)开发鲁棒的调制识别算法。调制识别的一方面是信号识别特征的提取。调制识别的最常见特征是瞬时相位,幅度和频率。但是,本文重点关注两个特征参数:相干性和熵。信号熵和相干函数显示了在存在HF噪声和多径情况下稳健识别HF调制类型的潜力。具体而言,表明相干性和熵的计算方法很重要,并且适当的计算可确保参数的稳定性。首次引入了一种称为相干中位数差异(CMD)的新度量,该度量提供了特定频率下相干优势对特定带宽中所有其他频率下相干优势的度量。

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